User Interface For Artifact Removal In An EEG

ABSTRACT

A method and system for a user interface for artifact removal in an EEG is disclosed herein. The invention allows an operator to select a plurality of artifacts to be automatically removed from an EEG recording using a user interface. The operator pushes a button on the user interface to apply a plurality of filters to remove the plurality of artifacts from the EEG and generate a clean EEG for viewing.

CROSS REFERENCES TO RELATED APPLICATIONS

The Present Application is a continuation application of U.S. patentapplication Ser. No. 14/583677, filed on Dec. 27, 2014, which is acontinuation application of U.S. patent application Ser. No. 13/684469,filed on Nov. 23, 2012, now U.S. Pat. No. 9,055,927, issued on Jun. 16,2015, which claims priority to U.S. Provisional Patent Application No.61/563839, filed on Nov. 28, 2011, now abandoned, U.S. patentapplication Ser. No. 13/684469 is also a continuation-in-partapplication of U.S. patent application Ser. No. 13/620784, filed on Sep.15, 2012, now U.S. Pat. No. 8,666,484, issued on Mar. 4, 2014, whichclaims priority to U.S. Provisional Patent Application No. 61/563731,filed on Nov. 25, 2011, now abandoned, and U.S. patent application Ser.No. 13/684469 is also a continuation-in-part application of U.S. patentapplication Ser. No. 13/542665, filed on Jul. 6, 2012, now abandoned,all of which are hereby incorporated by reference in their entireties.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to a method and system fordisplaying EEG data. More specifically, the present invention relates toanalyzing an EEG recording.

2. Description of the Related Art

An electroencephalogram (“EEG”) is a diagnostic tool that measures andrecords the electrical activity of a person's brain in order to evaluatecerebral functions. Multiple electrodes are attached to a person's headand connected to a machine by wires. The machine amplifies the signalsand records the electrical activity of a person's brain. The electricalactivity is produced by the summation of neural activity across aplurality of neurons. These neurons generate small electric voltagefields. The aggregate of these electric voltage fields create anelectrical reading which electrodes on the person's head are able todetect and record. An EEG is a superposition of multiple simplersignals. In a normal adult, the amplitude of an EEG signal typicallyranges from 1 micro-Volt to 100 micro-Volts, and the EEG signal isapproximately 10 to 20 milli-Volts when measured with subduralelectrodes. The monitoring of the amplitude and temporal dynamics of theelectrical signals provides information about the underlying neuralactivity and medical conditions of the person.

An EEG is performed to: diagnose epilepsy; verify problems with loss ofconsciousness or dementia; verify brain activity for a person in a coma;study sleep disorders, monitor brain activity during surgery, andadditional physical problems.

Multiple electrodes (typically 17-21, however there are standardpositions for at least 70) are attached to a person's head during anEEG. The electrodes are referenced by the position of the electrode inrelation to a lobe or area of a person's brain. The references are asfollows: F=frontal; Fp=frontopolar; T=temporal; C=central; P=parietal;O=occipital; and A=auricular (ear electrode). Numerals are used tofurther narrow the position and “z” points relate to electrode sites inthe midline of a person's head. An electrocardiogram (“EKG”) may alsoappear on an EEG display.

The EEG records brain waves from different amplifiers using variouscombinations of electrodes called montages. Montages are generallycreated to provide a clear picture of the spatial distribution of theEEG across the cortex. A montage is an electrical map obtained from aspatial array of recording electrodes and preferably refers to aparticular combination of electrodes examined at a particular point intime.

In bipolar montages, consecutive pairs of electrodes are linked byconnecting the electrode input 2 of one channel to input 1 of thesubsequent channel, so that adjacent channels have one electrode incommon. The bipolar chains of electrodes may be connected going fromfront to back (longitudinal) or from left to right (transverse). In abipolar montage signals between two active electrode sites are comparedresulting in the difference in activity recorded. Another type ofmontage is the referential montage or monopolar montage. In areferential montage, various electrodes are connected to input 1 of eachamplifier and a reference electrode is connected to input 2 of eachamplifier. In a reference montage, signals are collected at an activeelectrode site and compared to a common reference electrode.

Reference montages are good for determining the true amplitude andmorphology of a waveform. For temporal electrodes, CZ is usually a goodscalp reference.

Being able to locate the origin of electrical activity (“localization”)is critical to being able to analyze the EEG. Localization of normal orabnormal brain waves in bipolar montages is usually accomplished byidentifying “phase reversal,” a deflection of the two channels within achain pointing to opposite directions. In a referential montage, allchannels may show deflections in the same direction. If the electricalactivity at the active electrodes is positive when compared to theactivity at the reference electrode, the deflection will be downward.Electrodes where the electrical activity is the same as at the referenceelectrode will not show any deflection. In general, the electrode withthe largest upward deflection represents the maximum negative activityin a referential montage.

Some patterns indicate a tendency toward seizures in a person. Aphysician may refer to these waves as “epileptiform abnormalities” or“epilepsy waves.” These include spikes, sharp waves, and spike-and-wavedischarges. Spikes and sharp waves in a specific area of the brain, suchas the left temporal lobe, indicate that partial seizures might possiblycome from that area. Primary generalized epilepsy, on the other hand, issuggested by spike-and-wave discharges that are widely spread over bothhemispheres of the brain, especially if they begin in both hemispheresat the same time.

There are several types of brain waves: alpha waves, beta waves, deltawave, theta waves and gamma waves. Alpha waves have a frequency of 8 to12 Hertz (“Hz”). Alpha waves are normally found when a person is relaxedor in a waking state when a person's eyes are closed but the person ismentally alert. Alpha waves cease when a person's eyes are open or theperson is concentrating. Beta waves have a frequency of 13 Hz to 30 Hz.Beta waves are normally found when a person is alert, thinking,agitated, or has taken high doses of certain medicines. Delta waves havea frequency of less than 3 Hz. Delta waves are normally found only whena person is asleep (non-REM or dreamless sleep) or the person is a youngchild. Theta waves have a frequency of 4 Hz to 7 Hz. Theta waves arenormally found only when the person is asleep (dream or REM sleep) orthe person is a young child. Gamma waves have a frequency of 30 Hz to100 Hz. Gamma waves are normally found during higher mental activity andmotor functions.

The following definitions are used herein.

“Amplitude” refers to the vertical distance measured from the trough tothe maximal peak (negative or positive). It expresses information aboutthe size of the neuron population and its activation synchrony duringthe component generation.

The term “analogue to digital conversion” refers to when an analoguesignal is converted into a digital signal which can then be stored in acomputer for further processing. Analogue signals are “real world”signals (e.g., physiological signals such as electroencephalogram,electrocardiogram or electrooculogram). In order for them to be storedand manipulated by a computer, these signals must be converted into adiscrete digital form the computer can understand.

“Artifacts” are electrical signals detected along the scalp by an EEG,but that originate from non-cerebral origin. There are patient relatedartifacts (e.g., movement, sweating, ECG, eye movements) and technicalartifacts (50/60 Hz artifact, cable movements, electrode paste-related).

The term “differential amplifier” refers to the key toelectrophysiological equipment. It magnifies the difference between twoinputs (one amplifier per pair of electrodes).

“Duration” is the time interval from the beginning of the voltage changeto its return to the baseline. It is also a measurement of thesynchronous activation of neurons involved in the component generation.

“Electrode” refers to a conductor used to establish electrical contactwith a nonmetallic part of a circuit. EEG electrodes are small metaldiscs usually made of stainless steel, tin, gold or silver covered witha silver chloride coating. They are placed on the scalp in specialpositions.

“Electrode gel” acts as a malleable extension of the electrode, so thatthe movement of the electrodes leads is less likely to produceartifacts. The gel maximizes skin contact and allows for alow-resistance recording through the skin.

The term “electrode positioning” (10/20 system) refers to thestandardized placement of scalp electrodes for a classical EEGrecording. The essence of this system is the distance in percentages ofthe 10/20 range between Nasion-Inion and fixed points. These points aremarked as the Frontal pole (Fp), Central (C), Parietal (P), occipital(O), and Temporal (T). The midline electrodes are marked with asubscript z, which stands for zero. The odd numbers are used assubscript for points over the left hemisphere, and even numbers over theright

“Electroencephalogram” or “EEG” refers to the tracing of brain waves, byrecording the electrical activity of the brain from the scalp, made byan electroencephalograph.

“Electroencephalograph” refers to an apparatus for detecting andrecording brain waves (also called encephalograph).

“Epileptiform” refers to resembling that of epilepsy.

“Filtering” refers to a process that removes unwanted frequencies from asignal.

“Filters” are devices that alter the frequency composition of thesignal.

“Montage” means the placement of the electrodes. The EEG can bemonitored with either a bipolar montage or a referential one. Bipolarmeans that there are two electrodes per one channel, so there is areference electrode for each channel. The referential montage means thatthere is a common reference electrode for all the channels.

“Morphology” refers to the shape of the waveform. The shape of a wave oran EEG pattern is determined by the frequencies that combine to make upthe waveform and by their phase and voltage relationships. Wave patternscan be described as being: “Monomorphic”. Distinct EEG activityappearing to be composed of one dominant activity. “Polymorphic”.distinct EEG activity composed of multiple frequencies that combine toform a complex waveform. “Sinusoidal”. Waves resembling sine waves.Monomorphic activity usually is sinusoidal. “Transient”. An isolatedwave or pattern that is distinctly different from background activity.

“Spike” refers to a transient with a pointed peak and a duration from 20to under 70 msec.

The term “sharp wave” refers to a transient with a pointed peak andduration of 70-200 msec.

The term “neural network algorithms” refers to algorithms that identifysharp transients that have a high probability of being epileptiformabnormalities.

“Noise” refers to any unwanted signal that modifies the desired signal.It can have multiple sources.

“Periodicity” refers to the distribution of patterns or elements in time(e.g., the appearance of a particular EEG activity at more or lessregular intervals). The activity may be generalized, focal orlateralized.

An EEG epoch is an amplitude of a EEG signal as a function of time andfrequency.

Various techniques have been developed to present the EEG data to aphysician or technician. However, these techniques are still lacking.Learning what is an artifact and how to see what is in the underlyingsignal is one of the most difficult problems in EEG interpretation. Anumber of techniques have been developed for algorithmically removingartifact to produce a cleaner EEG, but in order for these to be adoptedcommercially it is necessary to develop a user interface that allows theuser to see how the original signal has evolved to the clean signal.

BRIEF SUMMARY OF THE INVENTION

The present invention provides a solution to this problem by providing auser interface for artifact removal in an EEG. This is important for twomain reasons. First it provides confidence to the user that the cleanerEEG correctly represents what would be present in the absence ofartifact. Secondly the user may want to see the original signal, or thesignal after only partial cleaning in order to determine if there isinformation present that is useful.

In the present invention a process of producing a “clean” EEG involves aseries of steps. For example artifacts related to electrical issuesmight be one step. Another step would remove eye blinks. Another stepmight remove surface muscle. Yet another step might remove effects oftongue movement. Each step is a kind of algorithmic filter, althoughthis is very different than the classic filters that remove everythingwithin a certain frequency range. Currently EEG is typically displayedas a series of traces organized by channel. Channels commonly representthe voltage difference between two scalp electrodes, but they can alsorepresent the differences between an electrode and an average or otheraggregation of a group of electrodes. The traces have a vertical axis ofvoltage and a horizontal axis of time. Sets of channels are displayed ona page, and a set of channels is called a montage.

The information displayed in a montage can commonly be filtered byremoving certain frequency ranges. There are also frequently otheroptions such as limiting “pen deflection” which limits the amplitude ofa trace and drawing a horizontal line until the amplitude is below thelimit.

With the introduction of artifact filters the user will need the abilityto select which artifact filters are being applied and have thatconfirmed on the display. In addition they will need the ability tosimultaneously show a set of traces for each channel representing theeffects of the artifact filters. One choice would be to show both theoriginal signal as well as the signal after applying the entire set ofselected filters. They may also want to see a trace with the differencebetween the original signal and the filtered signal. They may also wantto see traces showing the signal at different points in the process ofartifact filtering. For example they might want to see a trace with justthe muscle artifacts removed but leaving the eye blinks. In order toremove some artifacts like eye blinks the software might use specificrecognition algorithms that detect the pattern. In this case the usermay simply want to see an indication that an eye blink or other patternwas present while still removing the effects of the pattern from thetrace. (People reading EEGs use eye blinks as one way to tell that thepatient is awake, but the eye blink produces a large artifact obscuringother information on the channels it affects).

Another feature of the present invention is the ability to select colorsfor the various traces and the amount of darkness/emphasis. Some usersmay want the original signal to be primary with the artifact filteredtraces present in the background as reference. Other users may want oneof the filtered traces to be primary. Choice of colors is important forthis reason and also because a significant fraction of people are colorblind to certain colors.

Another aspect of the artifact filtering process is that it will breakthe signal into a set of underlying signals. This can be useful evenafter artifacts are removed in seeing the various components of the truesignal from the brain. For example there might be slow waves separatefrom individual epileptiform patterns. A user might want to choose tosee these components separately on a channel to make it easier to seethe various portions of the true signal. Doing this would likely nothave been useful prior to removing most significant artifacts.

Another aspect of the present invention is a single “button” thatapplies a set of pre-selected artifact filters in a standard programused to review EEG. The button allows a technician to toggle on and offto allow for filtered and unfiltered traces for review by thetechnician.

One aspect of the present invention is a method for analyzing an EEGrecording. The method includes generating an EEG recording from amachine comprising a plurality of electrodes, an amplifier andprocessor. The method also includes processing the EEG to create aprocessed EEG recording for analysis. The method also includesrecognizing a pattern in the processed EEG recording.

Another aspect of the present invention is a system for analyzing an EEGrecording. The system includes electrodes for generating a plurality ofEEG signals, at least one amplifier connected to each of the pluralityof electrodes by a plurality of wires to amplify each of the pluralityof EEG signals, a processor connected to the amplifier to generate anEEG recording from the plurality of EEG signals, a display connected tothe processor for displaying an EEG recording. The processor isconfigured to recognize a pattern in the processed EEG recording.

Yet another aspect of the present invention is a method for analyzing anEEG recording. The method includes generating an EEG recording from amachine comprising a plurality of electrodes, an amplifier andprocessor. The method also includes processing the EEG to create aprocessed EEG recording for analysis. The method also includes detectinga plurality of events in the processed EEG recording. The method alsoincludes presenting the plurality of events as an event density graph.

Another aspect of the present provides an EEG system and method thatoverlays a processed EEG report over a raw EEG report to permit aphysician or technician to clearly see the activity reported.

This embodiment provides the ability to select short overlapping epochswhere the results of artifact removal from each epoch is stitchedtogether with the result from the next and previous epoch. Thisstitching can be accomplished many ways, but in a preferred method thesignals from the two epochs are combined using a weighted average wherethe weight is proportional to the ratio of the distance to the epochcenters.

For example an epoch length of two seconds is selected with an increment(epoch step) of one second. Artifact removal using BSS and othertechniques is performed on a set of channels for seconds one and twoproducing a two second length “clean” result. Then artifact removal isperformed on seconds two and three producing an overlapping cleanresult. The results overlap in the second second of the record. For eachchannel, the weighted average of the two overlapping results produces afinal result without discontinuities. In the portion of the secondnearer the center of the first epoch the value from the first epoch isweighted higher, and likewise for the portion nearer the center of thesecond epoch. Those skilled in the pertinent art will recognize thatdifferent or variable epoch lengths or steps may be selected whilemoving through the record. Also a different stitching technique might beused.

One aspect of the present invention is a method for filtering artifactsfrom an EEG signal. The method includes generating an EEG signal from amachine comprising a plurality of electrodes, an amplifier andprocessor. The method also includes transforming the EEG signal from aset of channels into a plurality of epochs. Each of the plurality ofepochs has an epoch duration length of less than or equal to two secondsand an increment of less than or equal to one second. The method alsoincludes filtering artifacts from each of the plurality of epochs usinga blind source separation algorithm to generate a plurality of cleanepochs. The method also includes combining the plurality of clean epochsto generate a processed EEG recording.

Yet another aspect of the present invention is a method for filteringartifacts from an EEG signal using a blind source separation algorithm.The method includes generating an EEG signal from a machine comprising aplurality of electrodes, an amplifier and processor. The method alsoincludes transforming the EEG signal from a set of channels into aplurality of epochs. The method also includes filtering artifacts fromeach of the plurality of epochs using a blind source separationalgorithm to generate a plurality of clean epochs. The method alsoincludes combining the plurality of clean epochs to generate a processedEEG recording.

Yet another aspect of the present invention is a system for filteringartifacts from an EEG signal. The system includes electrodes, anamplifier, a processor and a display. The electrodes generate EEGsignals. The amplifier is connected to each of the electrodes by wiresand amplifies the EEG signals. The processor is connected to theamplifier to generate an EEG recording from the EEG signals. The displayis connected to the processor to display an EEG recording. The processoris configured to transform each of the plurality of EEG signals from aset of channels into a plurality of epochs, remove artifacts from eachof the plurality of epochs using a blind source separation algorithm togenerate a plurality of clean epochs, and combine the plurality of cleanepochs to generate a processed EEG recording for display.

Yet another aspect of the present invention is a method for filteringartifacts from an EEG signal using a artifact removal algorithm. Themethod includes generating an EEG signal from a machine comprising aplurality of electrodes, an amplifier and processor. The method alsoincludes transforming the EEG signal from a set of channels into aplurality of epochs. The method also includes filtering artifacts fromeach of the plurality of epochs using an artifact removal algorithm togenerate a plurality of clean epochs. The method also includes combiningthe plurality of clean epochs to generate a processed EEG recording.

Yet another aspect of the present invention is a method for filteringartifacts from an EEG signal by selecting an epoch time and increment.The method includes generating an EEG signal for a patient from amachine comprising a plurality of electrodes attached to the patient, anamplifier and processor. The method also includes selecting an epochtime length and an epoch time increment. The method also includesfiltering artifacts for each of a plurality of epochs using an artifactremoval algorithm to generate a plurality of clean epochs. The methodalso includes assigning a weighted average to each of the plurality ofclean epochs. The method also includes combining the plurality of cleanepochs to overlap to generate a processed EEG recording withoutdiscontinuities.

Yet another aspect of the present invention is a system for filteringartifacts from an EEG signal. The system includes electrodes, aprocessor, and a display. The electrodes generate EEG signals. Theprocessor is connected to the electrodes to generate an EEG recordingfrom the EEG signals. The display is connected to the processor anddisplays an EEG recording. The processor is configured to select anepoch time length and an epoch time increment, filter artifacts for eachof a plurality of epochs using an artifact removal algorithm to generatea plurality of clean epochs, assign a weighted average to each of theplurality of clean epochs, and combine the plurality of clean epochs tooverlap to generate a processed EEG recording without discontinuities.

Still another aspect of the present invention is a method for displayingEEG data. The method includes generating an original EEG report from anEEG signal. The original EEG report is generated from an EEG machinecomprising a plurality of electrodes and processor. The original EEGreport comprises a first plurality of channels. The method also includesperforming artifact reduction on the original EEG signal to generate aprocessed EEG report. The processed EEG report comprises a secondplurality of channels. The method also includes overlaying the processedEEG report on the original EEG report to generate a combined EEG report.An x-axis of the processed EEG report is aligned with an x-axis of theoriginal EEG report. A y-axis of the processed EEG report is alignedwith an y-axis of the original EEG report. The first plurality ofchannels of the original EEG report are equal to the second plurality ofchannels of the processed EEG report. The method also includesdisplaying the combined EEG report wherein the processed EEG report isvisually distinctive from the original EEG report. An activity at aspecific time on one channel of the first plurality of channels of theoriginal EEG report is identifiable on a corresponding channel of thesecond plurality of channels of the processed EEG report at the specifictime. The activity is preferably spikes, sharp waves, spike and wavedischarges, artifacts, and the like.

Still another aspect of the present invention is a method for displayinga combined EEG report. The method includes generating an original EEGreport from an EEG signal. The original EEG report is generated from anEEG machine comprising a plurality of electrodes and processor. Theoriginal EEG report comprises a first plurality of channels. The methodalso includes performing artifact reduction on the original EEG signalto generate a processed continuous EEG report. The processed EEG reportcomprises a second plurality of channels. The method also includesoverlaying the processed continuous EEG report on the original EEGreport to generate a combined EEG report. An x-axis of the processedcontinuous EEG report is aligned with an x-axis of the original EEGreport. A y-axis of the processed continuous EEG report is aligned withan y-axis of the original EEG report. The first plurality of channels ofthe original EEG report are equal to the second plurality of channels ofthe processed continuous EEG report. The method also includes displayingthe combined EEG report wherein the processed EEG report is visuallydistinctive from the original EEG report. An activity at a specific timeon one channel of the first plurality of channels of the original EEGreport is identifiable on a corresponding channel of the secondplurality of channels of the processed continuous EEG report at thespecific time.

Still another aspect of the present invention is a system for displayingEEG data. The system includes a patient component, a machine componentand a display screen. The patient component comprises a plurality ofelectrodes for generating an EEG signal. The EEG machine componentcomprises an amplifier and a processor. The processor is configured togenerate an original EEG report from an EEG signal. The original EEGreport comprises a first plurality of channels. The processor is alsoconfigured to perform artifact reduction on the original EEG signal togenerate a processed EEG report. The processed EEG report comprises asecond plurality of channels. The processor is also configured tooverlay the processed EEG report on the original EEG report to generatea combined EEG report. An x-axis of the processed EEG report is alignedwith an x-axis of the original EEG report. A y-axis of the processed EEGreport is aligned with an y-axis of the original EEG report. The firstplurality of channels of the original EEG report are equal to the secondplurality of channels of the processed EEG report. The display screendisplays the combined EGG report wherein the processed EEG report isvisually distinctive from the original EEG report, and wherein anactivity at a specific time on one channel of the first plurality ofchannels of the original EEG report is identifiable on a correspondingchannel of the second plurality of channels of the processed EEG reportat the specific time.

Having briefly described the present invention, the above and furtherobjects, features and advantages thereof will be recognized by thoseskilled in the pertinent art from the following detailed description ofthe invention when taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is an illustration of a portion of a raw EEG report havingnineteen channels.

FIG. 1A is an enlargement of circle 1A of FIG. 1.

FIG. 2 is an illustration of a portion of a processed EEG report havingnineteen channels in which epochs do not overlap.

FIG. 2A is an enlargement of circle 2A of FIG. 2.

FIG. 3 is an illustration of a portion of a processed continuous EEGreport in which sections of the epochs of the EEG report are stitched tooverlap.

FIG. 3A is an enlargement of circle 3A of FIG. 3.

FIG. 4 is an illustration of a portion of a combined EEG report having aprocessed EEG report overlay on a raw EEG report.

FIG. 4A is an enlargement of circle A of FIG. 4.

FIG. 4B is an enlargement of circle B of FIG. 4.

FIG. 4C is an enlargement of circle C of FIG. 4.

FIG. 5 is an illustration of a portion of processed continuous EEGreport in which sections of the epochs of the EEG report are stitched tooverlap.

FIG. 6 is a flow chart of a method for displaying EEG data.

FIG. 7 is a flow chart for a method of artifact reduction.

FIG. 8 is an illustration of an EEG system used on a patient.

FIG. 9 is a map for electrode placement for an EEG.

FIG. 10 is a detailed map for electrode placement for an EEG.

FIG. 9 is a map representing the international 10-20 electrode systemfor electrode placement for an EEG.

FIG. 10 is a detailed map representing the intermediate 10% electrodepositions, as standardized by the American ElectroencephalographicSociety, for electrode placement for an EEG.

FIG. 11 is a block diagram of an EEG machine component of an EEG system.

FIG. 12 is an illustration of isolated adjacent epochs.

FIG. 13 is an illustration of isolated adjacent epochs.

FIG. 14 is an illustration of epochs stitched together with anoverlapping portion.

FIG. 15 is an example of prior art combining of epochs resulting indiscontinuous or missing information from the processed and stitched EEGrecording.

FIG. 16 is a flow chart of a method for displaying EEG data.

FIG. 17 is a flow chart for a method of artifact reduction.

FIG. 18 is a block diagram of a system for analyzing an EEG recording.

FIG. 19 is an illustration of an analyzed EEG recording.

FIG. 20 is an illustration of an analyzed EEG recording.

FIG. 21 is an illustration of an analyzed EEG recording.

FIG. 22 is an illustration of an analyzed EEG recording.

FIG. 23 is an illustration of an analyzed EEG recording.

FIG. 24 is a flow chart of a general method.

FIG. 25 is a flow chart of a specific method.

FIG. 26 is an illustration of a CZ reference montage.

FIG. 27 is an illustration of an EEG recording containing a seizure, amuscle artifact and an eye movement artifact.

FIG. 28 is an illustration of the EEG recording of FIG. 15 with themuscle artifact removed.

FIG. 29 is an illustration of the EEG recording of FIG. 16 with the eyemovement artifact removed.

FIG. 30 is an illustration of spike detections indicative of a seizure.

FIG. 31 is an illustration of a paralytic EEG record for a patient for afirst time period of the EEG record after removing muscle artifactsusing a recorded montage.

FIG. 32 is an illustration of a paralytic EEG record for a patient for afirst time period of the EEG record after removing muscle artifactsusing a CZ reference montage.

FIG. 33 is an illustration of a paralytic EEG record for a patient for asecond time period of the EEG record after removing muscle artifactsusing a recorded montage.

FIG. 34 is an illustration of a paralytic EEG record for a patient for asecond time period of the EEG record after removing muscle artifactsusing a CZ reference montage.

FIG. 35 is an illustration of a paralytic EEG record for a patient for athird time period (the patient has been paralyzed so the muscle activityis absent) of the EEG record after removing muscle artifacts using arecorded montage.

FIG. 36 is an illustration of a paralytic EEG record for a patient for athird time period (the patient has been paralyzed so the muscle activityis absent) of the EEG record after removing muscle artifacts using a CZreference montage.

FIG. 37 is a flow chart of a general method for filtering artifacts froman EEG signal.

FIG. 38 is a flow chart of a specific method for filtering artifactsfrom an EEG signal.

DETAILED DESCRIPTION OF THE INVENTION

A raw or original EEG report 100 is shown in FIG. 1. The original EEGreport 100 has a plurality of channels FP1-Ref through to O2-Ref, shownat the Y axis 105 of the report. The X-axis of the report is time. Theoriginal EEG report 100 has not been subjected to artifact reduction.The original EEG report contains artifacts from various sources such asmuscle movement, eye movement, sweating, electrode cables and the like.However, the EEG may also have certain activity that a physician ortechnician is looking for from the EEG report in order to accuratelyanalyze the patient's brain activity. For example, the activity shown inFIG. 1A at a time 655.000 may represent a certain stage of brainactivity for the patient that is important to the physician ortechnician. However, normally, the physician or technician will notreview the raw EEG report 100 due to the presence of artifacts.

FIG. 2 is an illustration of a processed EEG report 110 of the originalEEG report 100 of FIG. 1 that has undergone artifact reduction and thestitching of epochs in order to recreate the EEG report. The processedEEG report 110 has a plurality of channels FP1-Ref through to O2-Ref,shown at the Y axis 115 of the report. The X-axis of the report is time.As shown in FIG. 2A, the processed EEG report 110 at time 655.000 isquite different in appearance than the original EEG report 100 at time655.000. This is primarily due to stitching of epochs to recreate theEEG report, however, if a physician or technician were only looking atthe processed EEG report 110, the physician or technician would not beaware of the true activity at time 655.000.

FIG. 3 is an illustration of a processed continuous EEG report 120 ofthe original EEG report 100 of FIG. 1 that has undergone artifactreduction and the stitching of overlapping epochs in order to recreatethe EEG report. The processed EEG report 120 has a plurality of channelsFP1-Ref through to O2-Ref, shown at the Y axis 125 of the report. TheX-axis of the report is time. As shown in FIG. 3A, the processed EEGreport 120 at time 655.000 is more similar in appearance to the originalEEG report 100 at time 655.000 than the processed EEG report 110 of FIG.2. However, there is still difficulty in analyzing a patient's brainactivity by switching back and forth from an original EEG report 100 toa processed EEG report 110 or a processed continuous EEG report 120.

FIG. 4 is an illustration of a combined EEG report 130 comprising theoriginal EEG report 100 and the processed EEG report 110. Theillustration of the combined EEG report 130 only has five channels inorder to clearly illustrate the invention, however, those skilled in thepertinent art will recognize that the combined EEG report 130 could havesixteen, twenty, twenty-seven or any number of channels withoutdeparting from the scope and spirit of the present invention.

As shown in FIGS. 4, 4A, 4B and 4C, the original EEG report 100 has afirst line style and the processed EEG report 110 has a second linestyle distinctive from the first line style in order to allow aphysician and technician to easily and visually distinguish between theoriginal EEG report 100 and the processed EEG report 110. In analternative embodiment, the original EEG report 100 has a first color(e.g., blue) and the processed EEG report 200 has a second color (e.g.red) distinctive from the first color in order to allow a physician andtechnician to easily and visually distinguish between the original EEGreport 100 and the processed EEG report 110.

As shown in FIG. 4 and specifically FIG. 4C, the channels of theoriginal EEG report 100 are aligned with the channels of the processedEEG report 110 in order to have y-axis 135 alignment.

As shown in FIG. 4 and specifically in FIG. 4A, the x-axis of theoriginal EEG report 100 are aligned with the x-axis of the processed EEGreport 110 in order to have time alignment of the two EEG reports in thecombined EEG report 130.

Further, the amplitudes for both the original EEG report 100 and theprocessed EEG report 110 are contained within each of the channels inorder to prevent overlapping of the signals.

As shown in FIG. 4B, the original EEG report 100 is quite different fromthe processed EEG report 110 and a physician or technician may beinterested in the activity shown in the original EEG report 100 ascompared to the processed EEG report 110.

Those skilled in the pertinent art will recognize that the processedcontinuous EEG report 120 may be substituted for the processed EEGreport 110 in FIG. 4 in order to demonstrate a comparison between theoriginal EEG report 100 and the processed continuous EEG report 120.

FIG. 5 is an illustration of an EEG report 140, based on the EEG report120 of FIG. 3, in which channels have been removed for a clearerillustration of channels. The illustration of the combined EEG report140 only has five channels in order to clearly illustrate the invention,however, those skilled in the pertinent art will recognize that thecombined EEG report 140 could have sixteen, twenty, twenty-seven or anynumber of channels without departing from the scope and spirit of thepresent invention.

A flow chart for a method 700 for displaying EEG data is shown in FIG.6. At block 701, an original EEG report is generated from an EEG signal.The original EEG report is generated from an EEG machine comprising aplurality of electrodes, an amplifier, and a processor. The original EEGreport comprises a first plurality of channels. At block 702, theoriginal EEG signal is partitioned from a set of channels into epochs ofwhich each has a predetermined duration length and an overlap increment.At block 703, artifact reduction is performed on the epochs to generateartifact reduced epochs. At block 704, the artifact reduced epochs arecombined with overlapping adjacent epochs for a continuous EEG recordingto generate a processed continuous EEG report. The stitched, overlappingepochs and continuous processed EEG report is displayed on a displayscreen, preferably a monitor. The stitched overlapping epochs andcontinuous processed EEG report are not missing timeframes fromstitching or creating discontinuities in the EEG report, which is readby a physician or technician. All of the brain activity remains sincethe epochs overlap. The brain activity is preferably spikes, sharpwaves, spike and wave discharges, artifacts, and the like.

FIG. 7 is a flow chart of a preferred method 800 for displaying EEGdata. At block 801, an original EEG report is generated from an EEGsignal for a patient from a machine preferably comprising electrodesattached to the patient, an amplifier and a processor. At block 802, theoriginal EEG signal is partitioned from a set of channels into aplurality of epochs. Each of the plurality of epochs having an epochduration length and an overlap increment. At block 803, a first artifactreduction is performed on the plurality of epochs to remove electrodeartifacts. At block 804, a second artifact reduction is performed on theplurality of epochs to remove muscle artifacts. At block 805, a thirdartifact reduction is performed on the plurality of epochs to remove eyemovement artifacts. At block 806, the plurality of epochs is combined tooverlap wherein each epoch of the plurality of epochs overlaps anadjacent epoch to form a processed continuous EEG report. At block 807,a processed continuous EEG recording is generated from the combinedepochs.

Each of the plurality of epochs preferably has an epoch duration lengthof two seconds and an increment of one second. Alternatively, each ofthe plurality of epochs has an epoch duration length of four seconds andan increment of two seconds. The artifact removal algorithm ispreferably a blind source separation algorithm. The blind sourceseparation algorithm is preferably a CCA algorithm or an ICA algorithm.The clean epochs are preferably combined using a weighted average andthe weight of the weighted average is preferably proportional to theratio of the distance to an epoch center.

As shown in FIG. 8, an EEG system is generally designated 20. The systempreferably includes a patient component 30, an EEG machine component 40and a display component 50. The patient component 30 includes aplurality of electrodes 35 a, 35 b, 35 c attached to the patient 15 andwired by cables 38 to the EEG machine component 40. The EEG machinecomponent 40 comprises a CPU 41 and an amplifier component 42. The EEGmachine component 40 is connected to the display component 50 fordisplay of the combined EEG reports, and for switching from a processedEEG report to the combined EEG reports, or from the processed EEG reportto an original EEG report. As shown in FIG. 11, the EEG machinecomponent 40 preferably includes a stitching engine 65, an artifactreduction engine 66, an overlay engine 67, a memory 61, a memorycontroller 62, a microprocessor 63, a DRAM 64, and an Input/Output 68.Those skilled in the pertinent art will recognize that the machinecomponent 40 may include other components without departing from thescope and spirit of the present invention.

A patient has a plurality of electrodes attached to the patient's headwith wires from the electrodes connected to an amplifier for amplifyingthe signal to a processor, which is used to analyze the signals from theelectrodes and create an EEG recording. The brain produces differentsignals at different points on a patient's head. Multiple electrodes arepositioned on a patient's head as shown in FIGS. 9 and 10. For example,Fp1 on FIG. 9 is represented in channel FP1-Ref on FIG. 5. The number ofelectrodes determines the number of channels for an EEG. A greaternumber of channels produce a more detailed representation of a patient'sbrain activity. Preferably, each amplifier 42 of an EEG machinecomponent 40 corresponds to two electrodes 35 attached to a patient's 15head. The output from an EEG machine component 40 is the difference inelectrical activity detected by the two electrodes. The placement ofeach electrode is critical for an EEG report since the closer theelectrode pairs are to each other, the less difference in the brainwavesthat are recorded by the EEG machine component 40. A more thoroughdescription of an electrode utilized with the present invention isdetailed in Wilson et al., U.S. Pat. No. 8,112,141 for a Method AndDevice For Quick Press On EEG Electrode, which is hereby incorporated byreference in its entirety. The EEG is optimized for automated artifactfiltering. The EEG recordings are then processed using neural networkalgorithms to generate a processed EEG recording, which is analyzed fordisplay.

Algorithms for removing artifact from EEG typically use Blind SourceSeparation (BSS) algorithms like CCA (canonical correlation analysis)and ICA (Independent Component Analysis) to transform the signals from aset of channels into a set of component waves or “sources.” The sourcesthat are judged as containing artifact are removed and the rest of thesources are reassembled into the channel set.

FIG. 12 is an isolated view of adjacent unprocessed epochs 1 and 2.Epoch 1 has an overlapping portion 3 and epoch 2 has an overlappingportion 4. In this example, the overlapping portions 3 and 4 areapproximately two seconds in length. Thus, overlapping portions 3 and 4represent the same timeframe (two seconds) for raw EEG recording.

FIG. 13 is an illustration of adjacent processed epochs 5 and 6.Artifact reduction has been performed on these epochs 5 and 6. Processedepochs 5 and 6 represent the same timeframe as unprocessed epochs 1 and2. Thus, epoch 5 is the result of artifact reduction of unprocessedepoch 1, and epoch 6 is the result of artifact reduction of unprocessedepoch 2. Processed epoch 5 has an overlapping portion 7 and processedepoch 6 has an overlapping portion 8. Thus, overlapping portions 7 and 8represent the same timeframe (two seconds) for the processed EEGrecording. Further, overlapping portion 7 is the same timeframe asoverlapping portion 3 and overlapping portion 8 is the same timeframe asoverlapping portion 4. Further overlapping portions 3, 4, 7 and 8represent all the same timeframe.

FIG. 14 is an illustration of the stitching of adjacent processed epochs5 and 6 into a section of continuous processed EEG recording 9. Portion10 is the overlapping portions 7 and 8 from adjacent processed epochs 5and 6. As shown, no information is lost, and the processed EEG recordingis continuous, without abrupt termination points where epochs have beenstitched together.

FIG. 15 is an illustration of the prior art approach of stitching ofepochs without overlapping portions. The section 12 of the processed EEGrecording has a stitching portion 11, which has changed from the sametimeframe of the processed epochs 5 and 6. The stitching portion 11 isdifferent from section 10 of FIG. 14.

A flow chart for a method 900 for displaying EEG data is shown in FIG.16. At block 901, an original EEG report is generated from an EEGsignal. The original EEG report is generated from an EEG machinecomprising a plurality of electrodes and processor. The original EEGreport comprises a first plurality of channels. At block 902, artifactreduction is performed on the original EEG signal to generate aprocessed EEG report. The processed EEG report comprises a secondplurality of channels. At block 903, the processed EEG report overlaysthe original EEG report to generate a combined EEG report. An x-axis ofthe processed EEG report is aligned with an x-axis of the original EEGreport. A y-axis of the processed EEG report is aligned with a y-axis ofthe original EEG report. The first plurality of channels of the originalEEG report are equal to the second plurality of channels of theprocessed EEG report. At block 904, the combined EEG report is displayedon a display screen, preferably a monitor. The processed EEG report isvisually distinctive from the original EEG report. An activity at aspecific time on one channel of the first plurality of channels of theoriginal EEG report is identifiable on a corresponding channel of thesecond plurality of channels of the processed EEG report at the specifictime. The activity is preferably spikes, sharp waves, spike and wavedischarges, artifacts, and the like

FIG. 17 is a flow chart of a preferred method 902 for artifact reductionof raw EEG data. At block 902 a, the original EEG signal is portionedfrom a set of channels into a plurality of epochs. Each of the pluralityof epochs having an epoch duration length and an overlap increment. Atblock 902 b, a first artifact reduction is performed on the plurality ofepochs to remove electrode artifacts. At block 902 c, a second artifactreduction is performed on the plurality of epochs to remove muscleartifacts. At block 502 d, a third artifact reduction is performed onthe plurality of epochs to remove eye movement artifacts. At block 902e, the plurality of epochs is combined to overlap wherein each epoch ofthe plurality of epochs overlaps an adjacent epoch to form a processedcontinuous EEG report.

Each of the plurality of epochs has an epoch duration length of twoseconds and an increment of one second. Alternatively, each of theplurality of epochs has an epoch duration length of four seconds and anincrement of two seconds. The artifact removal algorithm is preferably ablind source separation algorithm. The blind source separation algorithmis preferably a CCA algorithm or an ICA algorithm. The clean epochs arepreferably combined using a weighted average and the weight of theweighted average is preferably proportional to the ratio of the distanceto an epoch center.

FIG. 18 illustrates a system 25 for a user interface for automatedartifact filtering for an EEG. A patient 15 wears an electrode cap 31,consisting of a plurality of electrodes 35 a-35 c, attached to thepatient's head with wires 38 from the electrodes 35 connected to an EEGmachine component 40 which consists of an amplifier 42 for amplifyingthe signal to a computer 41 with a processor, which is used to analyzethe signals from the electrodes 35 and create an EEG recording 51, whichcan be viewed on a display 50. A button on computer 41, either through akeyboard or touchscreen button on display 50 allows for the applicationof a plurality of filters to remove the plurality of artifacts from theEEG and generate a clean EEG. A more thorough description of anelectrode utilized with the present invention is detailed in Wilson etal., U.S. Pat. No. 8,112,141 for a Method And Device For Quick Press OnEEG Electrode, which is hereby incorporated by reference in itsentirety. The EEG is optimized for automated artifact filtering. The EEGrecordings are then processed using neural network algorithms togenerate a processed EEG recording which is analyzed for display.

FIGS. 19-23 illustrate analyzed EEG recordings. An additionaldescription of analyzing EEG recordings is set forth in Wilson et al.,U.S. patent application Ser. No. 13/620855, filed on Sep. 15, 2012, fora Method And System For Analyzing An EEG Recording, which is herebyincorporated by reference in its entirety.

When the Easy SpikeReview program opens, the Overview window 200 isinitially presented, as shown in FIG. 19. The overview depicts averagesfrom the various spike foci detected by a spike detection mechanism. Tocreate these overview averages the spike detections are sorted bydetection foci (electrode) and then all detections at a particular focusare mathematically averaged. For example, the first column of EEGrepresents an average of 2969 events that had their maximum point ofdetection at the T3 electrode. The columns of the EEG are preferablyseparated from other columns by a thin band of white. Each EEG columnrepresents a distinct group average. The primary electrode focal pointof each average, and the number of detection events incorporated intoeach average, 205 are shown above the columns of EEG. Channels includingthe detection focal point electrode are highlighted red 215. As withevoked potentials, averaging multiple detections results in an increasein the signal-to-noise ratio and makes it easier to delineate the fieldof distribution of epileptiform abnormalities.

The various functions of the Easy SpikeReview window include the abilityto choose spike detections per page 223, an EEG voltage amplitudeselector 224, a montage selector 225, LFF (TC) 226, HFF 227, notch 228,and a custom filter 229. Navigation to other tabs not in the currentview is also possible with the forward and back tabs 222. If there'smore than one page of Overview averages, clicking on the bottom bar 230will page forward. Right-clicking on the montage bar 210 will showmontage controls.

The sensitivity of the SpikeDetector output can be dynamically adjustedduring the review process, which is done by using the detectionsensitivity slider 220 that is labeled. When Easy SpikeReview isinitially opened, the detection sensitivity slider 220 is set to the farleft position. In this position the SpikeDetector neural networkalgorithms identify sharp transients that have a high probability ofbeing epileptiform abnormalities: these are events the detector assigneda high probability of being a real epileptiform abnormality. The rate offalse positive detections at this setting is lowest. Thus, the ratio oftrue epileptiform signal to false positive noise is highest at thissetting. However, some spikes and sharp waves that are less well-formedmay not be evident with the slider set at its lowest sensitivity. Thedetector's sensitivity can be quickly adjusted by dragging the slider220 towards the right so that it is more sensitive and thus more likelyto identify less well-formed or lower amplitude transients. New groupsmay then appear in the overview display of spike averages. In concertwith the increase in true spike detections, there is also an increase infalse positive detections.

In records with rare epileptiform abnormalities or those in which theSpikeDetector neural networks, when set to lowest sensitivity, do notrecognize the epileptiform abnormalities well, switching to the highestsetting on the detection sensitivity slider 220 may allow visualizationof real epileptiform abnormalities. In such cases, identifying the rareevents often requires assessment of the individual raw detections. Thisis accomplished by either displaying all raw detections back-to-backfollowing the spike averages on the overview page, or by reviewing thedetections at each electrode location, such as in FIG. 20, byprogressively selecting the location tabs 221 at the top of the EEGwindow. Detections that have already been viewed are marked with atrailing asterisk 325 behind the time.

Clicking on any of the electrode location tabs 221 at the top of the EEGwindow will display the raw (non-averaged) spike detections 300 thatarose from that particular electrode location. The individual detectionsare separated by a thin band of white, and the detection point iscentered in a one second segment of EEG and indicated by a faintvertical gray line with a heading indicating the time of detection 305.Channels containing the electrode involved in the detection arehighlighted red 310. Left double-clicking with the mouse on anyindividual detection 335 will cause an expanded EEG view 400, as shownin FIG. 21, of that particular detection 335 to appear. Leftdouble-clicking on the expanded view 400 will return the user to adisplay of back-to-back individual detections 300.

When viewing individual spike detections (accessed from the tabs 221above the EEG window), exemplar spikes can be hand-marked byleft-clicking with the mouse on the desired example. A rectangleoutlining the chosen spike 330 will appear. Marking all or unmarking alldetections can be done with the Mark All or UnMark All buttons 315 onthe toolbar. Hand-marked detections will be included in the spikeaverages that appear in the FinalReport. These hand-marked events canalso be displayed back-to-back, as shown in FIG. 22, immediatelyfollowing their averages in FinalReport 500, and can be printed 523 forarchival purposes or for evaluation by another reviewer.

Clicking on FinalReport tab 528 at the top of the EEG window displays asummary of all hand-marked exemplar spike or sharp waves 510 at thefocus 505 chosen. The initial default view shows the mathematicalaverages of the user-chosen hand-marked events, sorted by electrodefocus 505. As explained, head voltage topograms and back-to-backindividual user-selected events are displayed by selecting menu optionsor via right mouse click choices. Voltage topograms are only createdwhen viewing the EEG in a referential montage. FIG. 23 is a printpreview view 600 of a FinalReport showing a group average of 18user-selected spikes 605 and constituent spikes 610 a-610 c. Uponexiting 522 the program, all changes are automatically saved, includinguser marked spikes and viewed events.

FIG. 24 is a flow chart of a general method 1000 for removing artifactsfrom an EEG recording. At block 1001, a plurality of artifacts isselected to be automatically removed from an EEG recording using a userinterface. At block 1002 an EEG is generated. At block 1003, a pluralityof filters is applied to remove the plurality of artifacts from the EEG.At block 1004, a clean EEG is generated.

FIG. 25 is a flow chart of another method 1100 for removing artifactsfrom an EEG recording. At block 1101, an EEG is generated from a machinecomprising a plurality of electrodes, an amplifier and processor. Atblock 1102, multiple filters are applied sequentially to removeartifacts from the EEG. At block 1103, a clean EEG is generated. Atblock 1104, the clean EEG is displayed.

FIG. 26 is an illustration of a CZ reference montage 1400.

In one example an algorithm called BSS-CCA is used to remove the effectsof muscle activity from the EEG. Using the algorithm on the recordedmontage will frequently not produce optimal results. In this case it isgenerally optimal to use a montage where the reference electrode is oneof the vertex electrodes such as CZ in the international 10-20 standard.In this algorithm the recorded montage would first be transformed into aCZ reference montage prior to artifact removal. In the event that thesignal at CZ indicates that it is not the best choice then the algorithmwould go down a list of possible reference electrodes in order to findone that is suitable.

It is possible to perform BSS-CCA directly on the user-selected montage.However this has two issues. First this requires doing an expensiveartifact removal process on each montage selected for viewing by theuser. Second the artifact removal will vary from one montage to another,and will only be optimal when a user selects a referential montage usingthe optimal reference. Since a montage that is required for reviewing anEEG is frequently not the same as the one that is optimal for removingartifact this is not a good solution.

The artifact removal algorithm is preferably a blind source separationalgorithm. The blind source separation algorithm is preferably a CCAalgorithm or an ICA algorithm.

FIGS. 27-29 illustrate how removing artifacts from the EEG signal allowfor a clearer illustration of a brain's true activity for the reader.FIG. 27 is an illustration of an EEG recording containing a seizure, amuscle artifact and an eye movement artifact 1500. FIG. 28 is anillustration of the EEG recording of FIG. 27 with the muscle artifactremoved 1600. FIG. 29 is an illustration of the EEG recording of FIG. 28with the eye movement artifact removed 1700.

FIG. 30 is an illustration of spike detections indicative of a seizure1800. Seizure probability 1810; Rhythmicity Spectrogram, lefthemisphere, 1-25 Hz 1820; Rhythmicity Spectrogram, right hemisphere,1-25 Hz 1830; Relative Asymmetry Spectrogram, Hemispheric, 0-18 Hz 1840;Peak Envelope, hemispheric, 2-20 Hz 1850; Spike Detections (count per 5second epoch) 1860; Chewing Artifact Probability 1870.

FIGS. 31, 33, and 35 are illustrations of a paralytic EEG record for apatient for three time periods (at the third time period the patient hasbeen paralyzed so the muscle activity is absent 2300) of an EEG recordafter removing muscle artifacts using a recorded montage. FIGS. 32, 34,and 36 are illustrations of a paralytic EEG record for a patient forthree time periods (at the third time period the patient has beenparalyzed so the muscle activity is absent 2400) of an EEG record afterremoving muscle artifacts using a CZ reference montage. The red is theoriginal signal 1905 and the black is the reconstruction 1910. Using therecorded montage, all of the brain activity is removed and the blackreconstruction appears almost flat 1900, 2100, 2300. However, using theCZ reference montage, the brain activity is retained and appears in thefirst two time periods 2000, 2200 similar to the third time period 2400when the patient is paralyzed.

Various artifact removal techniques are explained in U.S. ProvisionalPatent Application Nos. 61/563807, 61/563751, 61/563755, 61/563731,61/56376761/563776, 61/563796, and 61/563828, which are all herebyincorporated by reference in their entireties.

FIG. 37 is a flow chart of a general method 1200 for filtering artifactsfrom an EEG signal. At block 1201, an EEG signal is generated from amachine comprising a plurality of electrodes, an amplifier andprocessor. At block 1202, the EEG signal is transformed from a set ofchannels into a plurality of epochs. At block 1203, artifacts from eachof the plurality of epochs are filtered using an artifact removalalgorithm to generate a plurality of clean epochs. At block 1204, theclean epochs are combined to generate a processed EEG recording.

Each of the plurality of epochs has an epoch duration length of twoseconds and an increment of one second. Alternatively, each of theplurality of epochs has an epoch duration length of four seconds and anincrement of two seconds.

The artifact removal algorithm is preferably a blind source separationalgorithm. The blind source separation algorithm is preferably a CCAalgorithm or an ICA algorithm.

The clean epochs are preferably combined using a weighted average andthe weight of the weighted average is preferably proportional to theratio of the distance to an epoch center.

FIG. 38 is a flow chart of a specific method 1300 for filteringartifacts from an EEG signal. At block 1301, an EEG signal is generatedfrom a machine. At block 1302, an epoch time length and an epoch timeincrement are selected for the EEG signal. At block 1303, artifacts fromeach of the plurality of epochs are filtered using an artifact removalalgorithm. At block 1304, a plurality of clean epochs is generated fromthe artifact removed epochs. At block 1305, a weighted average isassigned to each of the plurality of clean epochs. At block 1306, theclean epochs are combined to generate a processed EEG recording.

Each of the plurality of epochs has an epoch duration length of twoseconds and an increment of one second. Alternatively, each of theplurality of epochs has an epoch duration length of four seconds and anincrement of two seconds.

The artifact removal algorithm is preferably a blind source separationalgorithm. The blind source separation algorithm is preferably a CCAalgorithm or an ICA algorithm.

The clean epochs are preferably combined using a weighted average andthe weight of the weighted average is preferably proportional to theratio of the distance to an epoch center.

From the foregoing it is believed that those skilled in the pertinentart will recognize the meritorious advancement of this invention andwill readily understand that while the present invention has beendescribed in association with a preferred embodiment thereof, and otherembodiments illustrated in the accompanying drawings, numerous changesmodification and substitutions of equivalents may be made thereinwithout departing from the spirit and scope of this invention which isintended to be unlimited by the foregoing except as may appear in thefollowing appended claim. Therefore, the embodiments of the invention inwhich an exclusive property or privilege is claimed are defined in thefollowing appended claims.

We claim as our invention:
 1. A method for removing artifacts in anelectroencephalogram (EEG) recording, the method comprising: generatingan EEG recording from a machine comprising a plurality of electrodes forgenerating a plurality of EEG signals, at least one amplifier connectedto each of the plurality of electrodes by a plurality of wires toamplify each of the plurality of EEG signals, a processor connected tothe amplifier to generate an EEG recording from the plurality of EEGsignals, and a display connected to the processor for displaying an EEGrecording; displaying the EEG recording on the display, the EEGrecording comprising a plurality of artifacts wherein the plurality ofartifacts comprises at least two of a muscle artifact, an eye movementartifact, an electrical artifact, a heartbeat artifact, a tonguemovement artifact, and a chewing artifact; selecting at least one of theplurality of artifacts to automatically be removed from the EEGrecording using a user interface on the display; pushing a button on acomputer to apply at least one filter of a plurality of filters toremove the at least one artifact of the plurality of artifacts from theEEG recording, wherein the button is a keyboard button or a touchscreenbutton, and wherein the processor is configured to apply at least onefilter program to remove a filter from the EEG recording; and generatinga filtered EEG recording on the display for viewing.
 2. The methodaccording to claim 1 further comprising selecting colors for traces andthe amount of darkness.
 3. The method according to claim 1 wherein theprocessor is configured to run a spike review program on the EEGrecording to detect a plurality of spikes on the EEG recording, sort thedetected plurality of spikes by each electrode of the plurality ofelectrodes, and mathematically average the detected plurality of spikesat each electrode to generate a plurality of overview averages, whereinthe user interface allows for display of each of the plurality ofoverview averages.
 4. A method for removing artifacts in anelectroencephalogram (EEG) recording, the method comprising: generatingan EEG recording from a machine comprising a plurality of electrodes forgenerating a plurality of EEG signals, at least one amplifier connectedto each of the plurality of electrodes by a plurality of wires toamplify each of the plurality of EEG signals, a processor connected tothe amplifier to generate an EEG recording from the plurality of EEGsignals, and a display connected to the processor for displaying an EEGrecording; displaying the EEG recording on the display, the EEGrecording comprising a plurality of artifacts wherein the plurality ofartifacts comprises at least two of a muscle artifact, an eye movementartifact, an electrical artifact, a heartbeat artifact, a tonguemovement artifact, and a chewing artifact; filtering the EEG recordingto remove a first artifact to generate a first filtered EEG recording toreplace the EEG recording on the display, wherein the processor isconfigured to apply a first filter program to the EEG recording;filtering the first filtered EEG recording to remove a second artifactto generate a second filtered EEG recording to replace the firstfiltered EEG recording on the display wherein the processor isconfigured to apply a second filter program to the EEG recording;filtering the second filtered EEG recording to remove a third artifactto generate a third filtered EEG recording to replace the secondfiltered EEG recording on the display wherein the processor isconfigured to apply a third filter program to the EEG recording;filtering the third filtered EEG recording to remove a fourth artifactto generate a fourth filtered EEG recording to replace the thirdfiltered EEG recording on the display wherein the processor isconfigured to apply a fourth filter program to the EEG recording; andgenerating a clean EEG recording for viewing from a last filtered EEGrecording. wherein each of the first artifact, the second artifact, thethird artifact and the fourth artifact is selected from the groupcomprising muscle artifact, eye movement artifact, electrical artifact,heartbeat artifact, tongue movement artifact, and chewing artifact.
 5. Amethod for displaying electroencephalogram (EEG) data, the methodcomprising: performing artifact reduction on an original EEG signalcomprising a first plurality of channels to generate a processedcontinuous EEG report, the processed continuous EEG report comprising asecond plurality of channels, wherein performing artifact reductioncomprises partitioning the original EEG signal into a plurality ofepochs, performing artifact reduction on the plurality of epochs togenerate a plurality of artifact reduced epochs, and combining theplurality of artifact reduced epochs to generate a processed EEGrecording, wherein each of the plurality of artifact reduced epochsoverlaps an adjacent artifact reduced epoch to produce a continuousprocessed EEG recording without discontinuities in the processed EEGrecording, wherein the plurality of artifact reduced epochs are combinedusing a weighted average wherein the weight of the epoch is proportionalto a ratio of a distance to an epoch center; overlaying the processedcontinuous EEG report on the original EEG report to generate a combinedEEG report, wherein an x-axis of the processed continuous EEG report isaligned with an x-axis of the original EEG report, wherein the secondplurality of channels of a y-axis of the processed continuous EEG reportis aligned with the first plurality of channels of a y-axis of theoriginal EEG report; and displaying the combined EEG report on a displayscreen of a monitor, the monitor in communication with the processor. 6.The method according to claim 5 wherein the artifact reduction is for atleast one of muscle artifact, eye movement artifact, electricalartifact, heartbeat artifact, tongue movement artifact, and chewingartifact.
 7. The method according to claim 5 wherein the combined EEGreport comprises the processed EEG report having a first color and theoriginal EEG report having a second color different than the firstcolor.
 8. The method according to claim 5 wherein the combined EEGreport comprises the processed EEG report having a first style and theoriginal EEG report having a second style different than the firststyle.
 9. The method according to claim 5 wherein the overlay of theprocessed EEG report on the original EEG report has the overlay of eachchannel of the second plurality of channels of the processed EEG reportwithin each corresponding channel of the first plurality of channels ofthe original EEG report.
 10. The method according to claim 5 furthercomprising switching from a display of the combined EEG report to adisplay of only the processed continuous EEG report.
 11. The methodaccording to claim 10 further comprising switching from the display ofthe processed continuous EEG report to a display of only the originalEEG report.